Position estimation is a key issue for an ALV Autonomous Land Vehicle) in navigating a mountainous area. The unevenness of the terrain makes mechanical velocity sensors inaccurate (due to wheel slippage), and the lack of appropriate landmarks complicates the problem. In this paper, we present a solution method using features of the skyline. The skyline from the vision system is assumed given, and compared with a computer map, called the CAD-MAP. The algorithm is composed of: a) Identification of the peak points in the camera skyline, b) Computing the ALV position for the identified peak points, and c) Searching for the corresponding peak point in the CAD-MAP. Heuristics for computational efficiency and solution accuracy are also included in the algorithm. To test the validity and effectiveness of the algorithm, numerous simulations were performed and analyzed.

This paper presents a computationally simple stereo vision method for detecting useful features of obstacles on the ground relevant to a mobile robot's navigation in an indoor environment. Enhanced time efficiency and reliability is achieved by introducing a geometrical image transformation and a frame-wise iterative edge image comparison scheme. The image transformation used in this paper relates each constant disparity value to an oblique plane at an elevation from the floor. The stereo correspondence method is devised by implementing a frame-wise AND operation based upon edge orientation and a subsequent pixel wise intensity correlation checking. This method is efficient in terms of computation time and capable of identifying isodisparity points, so that the height information of all the obstacle points above the floor can be determined. The obtained disparities are recorded on a local map to give complete obstacle features for mobile robot's path planning. Through a series of experiments performed under various environmental conditions, it is found that the proposed method can effectively be applied for locating obstacles of various heights in indoor navigation of mobile robots.

This special issue is concerned with the intelligent control of robots in the performance of manipulation tasks. First we will try to define what we mean by intelligent control and by manipulation tasks.

Unfortunately, intelligent control is a somewhat imprecise term, just like the word control itself, so that its meaning can vary widely depending on the application and on the writer's scientific discipline. In general terms, we can say that intelligent control implies some degree of autonomy in performing a task while accommodating uncertainty. In the control of sensor-based robot systems, we could characterize an intelligent controller as one with the following capabilities;

The problem associated with planning a collision-free path for a wheeled mobile robot (WMR) moving among obstacles in the workspace is investigated in this paper. A kinematic model, including the general nonholonomic constraint equation, is developed first, followed by the analysis of some general maneuvering characteristics of the WMR. The analytic solutions to the typical path curves, such as circle and straight line, which are important in the path planning problem, are also derived. From the analysis of the established kinematic model, some factors which affect the path planning problem for a WMR and therefore must be taken into account are revealed and the general description of the path planning problem for a WMR is formuated. In conclusion, a possible architecture of the algorithm for a practical WMR is presented.

A new approach to generating smooth piecewise local trajectories for mobile robots is proposed in this paper. Given the configurations (position and direction) of two points, we search for the trajectory that minimizes the integral of acceleration (tangential and normal). The resulting trajectory should not only be smooth but also safe in order to be applicable in real-life situations. Therefore, we investigate two different obstacle-avoidance constraints that satisfy the minimization problem. Unfortunately, in this case the problem becomes more complex and not suitable for real time implementations. Therefore, we introduce two simple solutions, based on the idea of polynomial fitting, to generate safe trajectories once a collision is detected with the original smooth trajectory. Simulation results of the different algorithms are presented.

This paper presents a method for the automatic generation of robotic assembly sequences based on the verification of a disassemblability for a part to be disassembled. To derive the disassemblability of a candidate part, we first inference collision free assembly directions by extracting separable directions for the part and calculating the separability which gives information as to how the part can be easily separated. Using the result, we determine the disassemblability defined in terms of the separability and stability costs. The separability cost represents a facility of the part disassembly operation, while the stability cost represents a degree of the stability for the base assembly motion which gives a guidance for design of jig/fixture. The proposed method provides a potentially local optimal solution for finding a cost effective assembly plan, and the feasibility of generating robot motion programs by evaluating separable directions in flexible manufacturing applications. A case study is given to illustrate the concepts and procedure of the proposed scheme.

In this paper, a numerical approach is proposed to solve the time-optimal path-planning (TOPP) problem of kinematically redundant manipulators between two end-points. The first step is to transform the TOPP problem into a nonlinear programming problem by an iterative procedure. Then an approach to find the initial feasible solutions of the problem is proposed. Since initial feasible solutions can be found easily, the optimization process of the nonlinear programming problem can be started from different points to find the global minimum. A planar three-link robotic manipulator is used to illustrate the validity of the proposed approach.

A local-remote telerobot control system is described which is being developed for time-delayed groundremote control of space telerobotic systems. The system includes a local site operator interface for interactive command building and sequencing for supervised autonomy and a remote site: the Modular Telerobot Task Execution System (MOTES), to provide the remote site task execution capability. The local site system also provides stereo graphics overlay on video with interactive update of the remote environmental model. The operator selects objects in the environment to interact with and skill types to specify the tasks to be performed, such as grasping a module or opening a door.

In the problem of automatically controlling a wheeled vehicle so that a given reference point on the vehicle follows a prescribed path, several factors determine how the task can be accomplished; they are the shape of the path, the initial orientation angle, the steering angle limit and the position of the reference point on the vehicle. If the required steering angle exceeds the limit set by the steering mechanism or the required orientation angle is discontinuous at any point along the path, then the path cannot be followed. This paper investigates this motion feasibility problem, taking steering angle limit into consideration. First of all, we determine the dependence of the continuity of the orientation angle, steering angle and their derivatives on the continuity of the reference path and its derivatives, then discuss .the relationship between the steering angle limit and the feasible deviation angle intervals. Furthermore, we analyze in detail two typical motions, namely straight line motion and circular motion; some simulation results have been given based on a practical vehicle dimension.

Learning control is a new approach to the probelm of skill refinement for robotic manipulators. It is considered to be a mathematical model of motor program learning for skilled motions in the central nervous system.

This paper proposes a class of learning control algorithms for improving operations of the robot arm under a geometrical end-point constraint at the next trial on the basis of the previous operation data. The command input torque is updated by a linear modification of present joint velocity errors deviated from the desired velocity trajectory in addition to the previous input. It is shown that motion trajectories approach an e-neighborhood of the desired one in the sense of squared integral norm provided the local feedback loop consists of both position and velocity feedbacks plus a feedback term of the error force vector between the reactive force and desired force on the end-point constrained surface. It is explored that various passivity properties of residual error dynamics of the manipulator play a crucial role in the proof of uniform boundedness and convergence of position and velocity trajectories.

It has been experimentally verified that the jerk of the desired trajectory adversely affects the performance of the tracking control algorithms for robotic manipulators. In this paper, we investigate the reasons behind this effect, and state the trajectory planning problem as an optimization problem that minimizes a norm of joint jerk over a prespecified Cartesian space trajectory. The necessary conditions are derived and a numerical algorithm is presented.

A nonlinear feedback control based on inverse dynamics is proposed for robots with flexible joints during constrained motion task execution. Based on constrained system formalism, the presented control scheme achieves simultaneous, independent control of both position and contact force at the robot end-effector. The method can be directly applied to robot control, or it can be used as the basis for developing other advanced control strategies. In this paper, a. feedforward controller is considered. Issues related to the practical application of the full inverse dynamics and feedforward control algorithms, such as evaluation of feedback variables, the use of predictors to eliminate the time delay of digital control, and the design of robust controllers, are discussed. The results of extensive numerical simulation are used to show the effectiveness of the proposed controllers and to compare their performances. It is shown that it is possible to achieve high precision tracking if the appropriate predictors are used to eliminate the effect of computational delay of the digital controller. Applying a straightforward approach for robustness of the proposed controllers has additionally improved the trajectory tracking accuracy.

A new method for computer forming of dynamic equations of open-chain mechanical robot configurations is presented. The algorithm used is of a numeric-iterative type, based on mathematical apparatus of screw theory, which has enabled elimination of the unnecessary computations in the process of dynamic model derivation. In addition to conventional kinematic schemes of robotic manipulators, the branched kinematic chains which have recently found their application in the locomotion of robotic mechanisms were also treated. Both the inverse and direct problems of dynamics were addressed. A comparative analysis was carried out of the numerical complexity of various existing algorithms of numeric-iterative type dealing with the problems of spatial active mechanisms dynamics. It has been shown that the proposed method regardless of its generality, approaches by its models complexity symbolic models, which are valid for particular robotic mechanisms only where they achieve a high degree of efficiency.

This paper addresses widely applicable methods for solving the kinematics problem of any class of serial-link robot manipulators. First, the position and orientation of the manipulator hand, the Jacobian matrix and their symbolic generation are clearly presented using recursive relations. Second, the inverse problem to such formulations is posed as an unconstrained non-linear optimization one, where numerical techniques for the overdetermined and underdetermined kinematic problems are considered separately to derive consistent arm solutions. On the basis of several proposals on step lengths involved to maintain good numerical stability, the results of computer simulation show that performance is sufficiently reliable.

The objective of this experimental research was to determine whether or not an integrated vision and robotic arm system, using grey level detection and a transportation model heuristic, could plan and execute its own point-to-point navigation. The heuristic is the shortest-route algorithm which deals with finding the smallest possible distance to visit multiple locations only once. The only point taught by a human operator was a starting position and all other points within the workspace, to be visited by the robotic arm to perform tasks such as screw-fastening, adhesive application and detailed inspection of assemblies, were learned by the system.

Two types of computer boards incorporating recently developed VLSI fuzzy inferencing chips have been developed to support the addition of qualitative reasoning capabilities to the real-time control of robotic systems. The design and operation of these boards are first reviewed and their use, in conjunction with our proposed Fuzzy Behaviorist approach, is discussed. This approach uses superposition of elemental sensor-based behaviors expressed in the Fuzzy Sets theoretic framework, to emulate "human-like" reasoning inrobotic systems.

A method is described to convert information available at manipulator programming level into trajectories which are suitable for tracking by a servo control system. This process generates trajectories in real time which comply with general dynamic and kinematic constraints. Tracking accuracy will depend mainly on the acceleration demand of the nominal trajectory setpoints - the actuator output demands, in particular, must remain bounded. Our scheme takes into consideration at the trajectory computation level the dynamics of the underlying system, dynamically available information acquired through sensors, and various types of constraints, such as manipulators. It has been developed in the context of a multi-manipulator programming and control system called Kali and developed at McGill University.

This paper presents an algorithm that solves the inverse kinematics problem of all six degrees of freedom manipulators, “general” or “special”. A manipulator is represented by a chain of characters that symbolizes the position of prismatic and revolute joints in the manipulator and the special geometry that may exist between its joint axes. One form of the loop closure equation is chosen and the Raghavan and Roth method is used to obtain symbolically a square matrix. The determinant of this matrix yields the characteristic polynomial of the manipulator in one of the kinematic variables. As an example of the use of this algorithm we present the solution to the inverse kinematics problem of the GMF Arc Mate welding manipulator. In spite of its geometry, this industrial manipulator has a non-trivial solution to its inverse kinematics problem.